I'd focus on what Tesla will be doing for a "budget" version. Something the upper middle class can afford. The Tesla is already advanced, now imagine the highest end electronic center console with all the navigation/music/video done better then ever before.

My main PC died. It was an HP Pavilion I bought back in May 2010. This time I went with a local custom PC maker. It's more expensive, but it should run a lot quieter and it's the latest core i7 and nVidia GEForce GTX 660 graphics, 16GB RAM.

The main reason I love Google Chrome is that it syncs my bookmarks, passwords across all machines. All I have to do is login to a new machine with my Google account and boom, all my bookkmarks and passwords are synced. It's beautiful.

Here's a UHDTV. Ultra High Definition TV. No use trying to find video of it, you can't see the difference unless you have the TV already. And if you did already have the TV then why would you want to see what it looks like when you already know?

Look at any Facebook photo album, and there’s a good chance Facebook has already figured out who’s who in the pictures and has attached names to the faces, even if the original uploader did not.

It’s able to do that by using special computer programs that match faces in photos to faces its users have already identified.

Now, law enforcement agencies are using the same kind of technology to identify criminal suspects caught on camera.

There is a 60 percent chance that an average-quality surveillance photo could be matched to a photo of the same person in a mugshot or driver’s license picture database, according to Michigan State University computer science Professor Anil K. Jain.

With better, higher-resolution surveillance photos, accurate matching can approach 100 percent. “It all depends on the quality of the image you have acquired,” Jain said.

To test the technology, Jain added a high school yearbook photo of one of the Boston Marathon bombing suspects to a database of 1 million photos taken for Florida driver’s licenses.

Using off-the-shelf software sold to police departments, Jain compared a fuzzy FBI image of the suspect at the marathon to the huge database of photos. The software picked the yearbook photo as the No. 1 match.Jain said the software uses statistical methods to identify and extract tiny groups of pixels that represent unique parts of significant facial features such as eyes, noses and mouths.

This reduces the number of pixels that need to be compared from over a million to just a few, making matches against millions of photos much easier.Different software companies use different approaches, but the trick is to “find the right features that don’t change very much based on the conditions under which the [surveillance] photo was taken,” Jain said.So good software will be able to match a head-on mugshot taken under controlled lighting to an odd-angled photo grabbed from fuzzy video.

Under real-world circumstances, the computer typically narrows a suspect’s photo to the 100 or so best matches, ranked by probable accuracy. “It’s much easier for a human being to look at 100 photos than 7 million,” Jain said.

The SmartWatch - wristwatch, computer, phone, camera, etc. Tech has been out there for years, but smaller and smaller components are making it more practical.. Look for it to drive advances in image display. It obviously can't be too big to use as a wristwatch, so the display size is currently limited. But I expect display projection in some form to be the next big tech on the horizon.